527 research outputs found

    Unforeseen misuses of bed nets in fishing villages along Lake Victoria

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    <p>Abstract</p> <p>Background</p> <p>To combat malaria, the Kenya Ministry of Health and nongovernmental organizations (NGOs) have distributed insecticide-treated nets (ITNs) for use over beds, with coverage for children under five years of age increasing rapidly. Nevertheless, residents of fishing villages have started to use these bed nets for drying fish and fishing in Lake Victoria. This study investigated the extent of bed net misuse in fishing villages.</p> <p>Methods</p> <p>Seven fishing villages along the lake were surveyed to estimate how widely bed nets were being used for fishing and drying fish. Villagers were asked why they used the bed nets for such purposes.</p> <p>Results</p> <p>In total, 283 bed nets were being used for drying fish. Of these, 239 were long-lasting insecticidal bed nets (LLIN) and 44 were non-long-lasting insecticidal bed nets (NLLIN). Further, 72 of the 283 bed nets were also being used for fishing. The most popular reasons were because the bed nets were inexpensive or free and because fish dried faster on the nets. LLINs were preferred to NLLINs for fishing and drying fish.</p> <p>Conclusion</p> <p>There is considerable misuse of bed nets for drying fish and fishing. Many villagers are not yet fully convinced of the effectiveness of LLINs for malaria prevention. Such misuses may hamper the efforts of NGOs and governmental health organizations.</p

    Malaria Vectors in Lake Victoria and Adjacent Habitats in Western Kenya

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    The prevalence of malaria among the residents of the Lake Victoria basin remains high. The environment associated with the lake may maintain a high number of malaria vectors. Lake habitats including water hyacinths have been suspected to be the source of vectors. This study investigated whether malaria vectors breed in the lake habitats and adjacent backwater pools. Anopheline larvae were collected within the littoral zone of the lake and adjacent pools located along approximately 24.3 km of the lakeshore in western Kenya, and their breeding sites characterized. Three primary vector species, Anopheles arabiensis, Anopheles gambiae s.s. and Anopheles funestus s.s., and three potential vectors, were found in the lake habitats. Unexpectedly, An. arabiensis was the most dominant vector species in the lake sampling sites. Its habitats were uncovered or covered with short grass. A potential secondary malaria vector, Anopheles rivulorum, dominated the water hyacinths in the lake. Most breeding sites in the lake were limited to areas that were surrounded by tall emergent plants, including trees, and those not exposed to waves. Nearly half of adjacent habitats were lagoons that were separated from the lake by sand bars. Lagoons contained a variety of microhabitats. Anopheles arabiensis dominated open habitats, whereas An. funestus s.s. was found mainly in vegetated habitats in lagoons. The current study confirmed that several breeding sites are associated with Lake Victoria. Given that Lake Victoria is the second largest lake in the world, the lake related habitats must be extensive; therefore, making targeted vector control difficult. Further exploration is necessary to estimate the effects of lake associated habitats on malaria transmission so as to inform a rational decision-making process for vector control

    Insecticide-treated net use before and after mass distribution in a fishing community along Lake Victoria, Kenya: successes and unavoidable pitfalls

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    Abstract Background Insecticide-treated nets (ITNs) have proven instrumental in the successful reduction of malaria incidence in holoendemic regions during the past decade. As distribution of ITNs throughout sub-Saharan Africa (SSA) is being scaled up, maintaining maximal levels of coverage will be necessary to sustain current gains. The effectiveness of mass distribution of ITNs, requires careful analysis of successes and failures if impacts are to be sustained over the long term. Methods Mass distribution of ITNs to a rural Kenyan community along Lake Victoria was performed in early 2011. Surveyors collected data on ITN use both before and one year following this distribution. At both times, household representatives were asked to provide a complete accounting of ITNs within the dwelling, the location of each net, and the ages and genders of each person who slept under that net the previous night. Other data on household material possessions, education levels and occupations were recorded. Information on malaria preventative factors such as ceiling nets and indoor residual spraying was noted. Basic information on malaria knowledge and health-seeking behaviours was also collected. Patterns of ITN use before and one year following net distribution were compared using spatial and multi-variable statistical methods. Associations of ITN use with various individual, household, demographic and malaria related factors were tested using logistic regression. Results After infancy (<1 year), ITN use sharply declined until the late teenage years then began to rise again, plateauing at 30 years of age. Males were less likely to use ITNs than females. Prior to distribution, socio-economic factors such as parental education and occupation were associated with ITN use. Following distribution, ITN use was similar across social groups. Household factors such as availability of nets and sleeping arrangements still reduced consistent net use, however. Conclusions Comprehensive, direct-to-household, mass distribution of ITNs was effective in rapidly scaling up coverage, with use being maintained at a high level at least one year following the intervention. Free distribution of ITNs through direct-to-household distribution method can eliminate important constraints in determining consistent ITN use, thus enhancing the sustainability of effective intervention campaigns.http://deepblue.lib.umich.edu/bitstream/2027.42/111296/1/12936_2014_Article_3656.pd

    Topography-derived wetness indices are associated with household-level malaria risk in two communities in the western Kenyan highlands

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    <p>Abstract</p> <p>Background</p> <p>Transmission of <it>Plasmodium falciparum </it>generally decreases with increasing elevation, in part because lower temperature slows the development of both parasites and mosquitoes. However, other aspects of the terrain, such as the shape of the land, may affect habitat suitability for <it>Anopheles </it>breeding and thus risk of malaria transmission. Understanding these local topographic effects may permit prediction of regions at high risk of malaria within the highlands at small spatial scales.</p> <p>Methods</p> <p>Hydrologic modelling techniques were adapted to predict the flow of water across the landscape surrounding households in two communities in the western Kenyan highlands. These surface analyses were used to generate indices describing predicted water accumulation in regions surrounding the study area. Households with and without malaria were compared for their proximity to regions of high and low predicted wetness. Predicted wetness and elevation variables were entered into bivariate and multivariate regression models to examine whether significant associations with malaria were observable at small spatial scales.</p> <p>Results</p> <p>On average, malaria case households (n = 423) were located 280 m closer to regions with very high wetness indices than non-malaria "control" households (n = 895) (t = 10.35, p < 0.0001). Distance to high wetness indices remained an independent predictor of risk after controlling for household elevation in multivariate regression (OR = 0.93 [95% confidence interval = 0.89–0.96] for a 100 m increase in distance). For every 10 m increase in household elevation, there was a 12% decrease in the odds of the house having a malaria case (OR = 0.88 [0.85–0.90]). However, after controlling for distance to regions of high predicted wetness and the community in which the house was located, this reduction in malaria risk was not statistically significant (OR = 0.98 [0.94–1.03]).</p> <p>Conclusion</p> <p>Proximity to terrain with high predicted water accumulation was significantly and consistently associated with increased household-level malaria incidence, even at small spatial scales with little variation in elevation variables. These results suggest that high wetness indices are not merely proxies for valley bottoms, and hydrologic flow models may prove valuable for predicting areas of high malaria risk in highland regions. Application in areas where malaria surveillance is limited could identify households at higher risk and help focus interventions.</p

    Spatial distribution and habitat characterisation of Anopheles larvae along the Kenyan coast

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    Background & objectives: A study was conducted to characterise larval habitats and to determine spatialheterogeneity of the Anopheles mosquito larvae. The study was conducted from May to June 1999 innine villages along the Kenyan coast.Methods: Aquatic habitats were sampled by use of standard dipping technique. The habitats werecharacterised based on size, pH, distance to the nearest house, coverage of canopy, surface debris, algaeand emergent plants, turbidity, substrate, and habitat type.Results: A total of 110 aquatic habitats like stream pools (n = 10); puddles (n = 65); tire tracks (n =5); ponds (n = 5) and swamps (n = 25) were sampled in nine villages located in three districts of theKenyan coast. A total of 7,263 Anopheles mosquito larvae were collected, 63.9% were early instarsand 36.1% were late instars. Morphological identification of the III and IV instar larvae by use ofmicroscopy yielded 90.66% (n = 2,377) Anopheles gambiae Complex, 0.88% (n = 23) An. funestus,An. coustani 7.63% (n = 200), An. rivulorum 0.42% (n = 11), An. pharoensis 0.19% (n = 5), An.swahilicus 0.08% (n = 2), An. wilsoni 0.04% (n = 1) and 0.11% (n = 3) were unidentified. A subset ofthe An. gambiae Complex larvae identified morphologically, was further analysed using rDNA-PCRtechnique resulting in 68.22% (n = 1,290) An. gambiae s.s., 7.93% (n = 150) An. arabiensis and 23.85%(n = 451) An. merus. Multiple logistic regression model showed that emergent plants (p = 0.019), andfloating debris (p = 0.038) were the best predictors of An. gambiae larval abundance in these habitats.Interpretation & conclusion: Habitat type, floating debris and emergent plants were found to be thekey factors determining the presence of Anopheles larvae in the habitats. For effective larval control,the type of habitat should be considered and most productive habitat type be given a priority in themosquito abatement programm
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